28 / 161
Conformational Ensembles from Experimental Data
and Computer Simulations
Monday Speaker Abstracts
24
Birth of the Cool: Protein Allostery by Multi-temperature Multi-conformer X-ray
Crystallography
James Fraser
University of California, San Francisco, San Francisco, CA, USA
No Abstract
Hybrid Models and Bayesian Analysis of Individual EM Images: An Alternative for
Challenging EM Data
Pilar Cossio
1,2
, Gerhard Hummer
2
.
1
University of Antioquia, Medellin, Colombia,
2
Max Planck Institute of Biophysics, Frankfurt,
Germany.
Electron microscopy (EM) provides projections images of individual biomolecules. Unhampered
by the need to obtain crystals, and without the system size limits faced in nuclear magnetic
resonance studies, EM is a true single-molecule technique at near-native conditions. To harness
this potential, we developed a method to extract structural information from individual images of
dynamic molecular assemblies. The Bayesian inference of EM (BioEM) [1] method uses a
likelihood-based probabilistic measure to quantify the degree of consistency between each EM
image and given model ensembles. These structural models can be constructed using hybrid-
modeling or obtained from molecular dynamics simulations. To analyze EM images of highly
flexible molecules, we propose an ensemble refinement procedure, and validate it with weighted
ensembles from simulations and synthetic images of the ESCRT I-II supercomplex. Both the size
of the ensemble and its structural members are identified correctly.
The BioEM posterior calculation is performed with a highly parallelized, GPUaccelerated
computer software [2] resulting in a nearly ideal scaling both on pure CPU and on CPU+GPU
architectures. This enables Bayesian analysis of tens of thousands of images in a reasonable time,
and offers an alternative to 3D reconstruction methods by its ability to extract accurate
population distributions for highly flexible structures and their assemblies.
[1] Cossio, Hummer. (2013) J. Struct. Biol. 184: 427-37.
[2] Cossio, et al. (2017) Compu. Phys. Commun. 210, 163-171.